docs: def peptides_to_network_input(self, peptides):
          """
          Encode peptides to the fixed-length encoding expected by the neural
          network (which depends on the architecture).
          
          Parameters
          ----------
          peptides : EncodableSequences or list of string
  
          Returns
          -------
          numpy.array
          """
          encoder = EncodableSequences.create(peptides)
          if (self.hyperparameters['peptide_amino_acid_encoding'] == "embedding"):
              encoded = encoder.variable_length_to_fixed_length_categorical(
                  max_length=self.hyperparameters['kmer_size'],
                  **self.input_encoding_hyperparameter_defaults.subselect(
                      self.hyperparameters))
          elif (
                  self.hyperparameters['peptide_amino_acid_encoding'] in
                      available_vector_encodings()):
              encoded = encoder.variable_length_to_fixed_length_vector_encoding(
                  self.hyperparameters['peptide_amino_acid_encoding'],
                  max_length=self.hyperparameters['kmer_size'],
                  **self.input_encoding_hyperparameter_defaults.subselect(
                      self.hyperparameters))
          else:
              raise ValueError("Unsupported peptide_amino_acid_encoding: %s" %
                               self.hyperparameters['peptide_amino_acid_encoding'])
          assert len(encoded) == len(peptides)
          return encoded